Modeling different discrete memristive sine maps and its parameter identification

Peng, Yuexi; Lan, Zixin; Li, Wenhan; Li, You; Peng, Jinzhang

doi:10.1140/epjs/s11734-022-00559-w

Cited by 11 publications

(4 citation statements)

References 41 publications

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“…At present, memristor-based nonlinear systems design is a hot topic. Although there are many different aspects about memristor-based nonlinear chaotic systems reported, such as a memristor-based neural system [1], multistability [8], synchronization [11], and discrete memristor [19], some of the memristor-based applications are not discussed, such as logical circuit, storage circuit, and artificial neuron system. Meanwhile, physical memristor devices [17] should receive more attention in the future since they will ultimately enable the realization of commercial applications.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…Peng et al [19] introduced three discrete memristors into a classical sine map after summarizing their characteristics, and then three different kinds of two-dimensional discrete memristive sine maps were designed. Dynamical analysis results demonstrated that the proposed method can expand the scope of chaos and improve the value of the maximum Lyapunov exponent.…”

Section: Discrete Memristor Chaotic Mapsmentioning

confidence: 99%

“…Additionally, the tools for memristor models should be diversified, such as fractional-order derivative, fractional-order difference, analog circuit, and digital circuits. Therefore, memristor-based studies are collected in this volume, including neural systems [1][2][3], multistability and hidden dynamics [4][5][6][7][8][9][10], synchronization controller [11,12], circuits [13][14][15][16][17][18], discrete memristor chaotic maps [19][20][21][22][23], and image encryption applications [24,25]. Some of the contributions discuss several aspects.…”

Section: Introductionmentioning

confidence: 99%

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Novel memristor and memristor-based applications

Wang

Banerjee

et al. 2022

Eur. Phys. J. Spec. Top.

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This special issue presents 25 papers regarding memristor systems and their applications. Part of the manuscripts are about memristor-based neural systems, and the systems show rich dynamics. Multistability in memristive systems has aroused much interest, and nonlinear behaviors, such as hidden attractors, extreme multistability, and transient chaotic transition, are observed. There are also two works investigating controllers of fractional-order memristor chaotic systems and several for circuit implementation of memristor chaotic systems. As new research, discrete memristor chaotic maps are reported and show potential application value in the future. Finally, there are two papers about the application of memristive chaotic systems to image encryption fields, indicating that memristive chaotic systems can be used in the information security field.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Discrete Memristor Chaotic Mapsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel memristor and memristor-based applications

Wang

Banerjee

et al. 2022

Eur. Phys. J. Spec. Top.

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“…Peng et al gave three 2D memristive sine maps by introducing three discrete memristor models into the sine map in Ref. [23]. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Extremely hidden multi-stability in a class of two-dimensional maps with a cosine memristor

et al. 2022

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In this work, we present a class of two-dimensional memristive maps with a cosine memristor. The memristive maps do not have any fixed points, so they belong to the category of nonlinear maps with hidden attractors. The rich dynamical behaviors of these maps are demonstrated and investigated using different numerical tools, including phase portrait, basins of attraction, bifurcation diagram, and Lyapunov exponents. The two-parameter bifurcation analysis of the memristive map has been carried out to reveal the bifurcation mechanism of the dynamical behaviors. Based on our extensive simulation studies, the proposed memristive maps can produce hidden periodic, chaotic, and hyper-chaotic attractors. They can exhibit extremely hidden multi-stability, namely the coexistence of infinite hidden attractors, rarely shown in memristive maps. Potentially, this work can be used for secure communication, such as data and image encryption.

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